Consumer Perceptions of AI-Based Personalization: A Dataset on Customer Experience, Loyalty, Purchasing Decisions, and System Quality. Q1-Q2 2026

This dataset contains 315 valid responses collected during the first and second quarters (Q1–Q2) of 2026 to support research on the relationships among Artificial Intelligence (AI)-based Personalization, Customer Experience, Loyalty, Purchasing Decision, and System Quality. The dataset was developed to provide empirical evidence regarding the role of AI-driven personalization in shaping customer perceptions, behavioral intentions, and purchasing outcomes within digital service environments. The respondent profile consists of 204 males (64.8%) and 111 females (35.2%). The majority of respondents were aged 17–25 years (49.5%), followed by respondents aged 26–30 years (19.4%) and respondents aged 31–45 years (18.1%). The remaining respondents were over 50 years of age. This demographic composition reflects a sample largely dominated by young adults who are actively engaged with digital technologies and AI-enabled services. The dataset includes demographic information as well as measurements of five key constructs: AI-based Personalization, Customer Experience, Loyalty, Purchasing Decision, and System Quality. These data are suitable for a wide range of analytical approaches, including descriptive statistics, regression analysis, machine learning techniques, and structural equation modeling (SEM). Researchers, practitioners, and policymakers may utilize this dataset to investigate the influence of AI-enabled personalization on customer experience, loyalty formation, purchasing behavior, and perceptions of system quality. Furthermore, the dataset offers opportunities for comparative studies, predictive modeling, and the advancement of knowledge on consumer behavior within increasingly AI-driven digital ecosystems.